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Robust Mechanism Synthesis with Random and Interval Variables
Mechanism and Machine Theory
  • Xiaoping Du, Missouri University of Science and Technology
  • Pavan Kumar Venigella
  • Deshun Liu
Abstract
Robust mechanism synthesis minimizes the impact of uncertainties on the mechanism performance. It has traditionally been performed by either a probabilistic approach or a worst case approach. Both approaches treat uncertainty as either random variables or interval variables. In reality, uncertainty can be a mixture of both. In this paper, methods are developed for robustness assessment and robust mechanism synthesis when random and interval variables are involved. Monte Carlo simulation is used to perform robustness assessment under an optimization framework for mechanism synthesis.
Department(s)
Mechanical and Aerospace Engineering
Sponsor(s)
Missouri University of Science and Technology. Intelligent Systems Center
National Natural Science Foundation (China)
National Science Foundation (U.S.)
Keywords and Phrases
  • Optimization,
  • Robustness,
  • Synthesis
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2009 Elsevier, All rights reserved.
Publication Date
7-1-2009
Citation Information
Xiaoping Du, Pavan Kumar Venigella and Deshun Liu. "Robust Mechanism Synthesis with Random and Interval Variables" Mechanism and Machine Theory (2009)
Available at: http://works.bepress.com/xiaoping-du/71/